This invention relates generally to the field of geophysical prospecting. More particularly, the invention is a method for analyzing reflection curvature in seismic data volumes.
Seismic reflection geometry can play a major role in the identification and delineation of reservoir intervals. In particular, reflection curvature, also referred to as moundedness, can be a particularly useful characteristic for identifying clastic and carbonate reservoirs. This is because mounds can indicate certain depositional or compaction characteristics.
Depositional and compaction mechanisms for the creation of mounded geometries are related and the seismic expression of the resulting deposit can thus be exploited in the hydrocarbon exploration and production work process. Specifically, the identification and mapping of qualitatively mounded geometries can lead to the delineation of strongly reservoir-prone intervals.
Reflection curvature, in general, can also be employed to quantitatively estimate fracture density in carbonate reservoirs. In carbonate reservoirs, a high fracture density can mean increased producibility of hydrocarbons from that region and is often accompanied by extreme values of seismic reflection curvature. This would thus be of interest to seismic interpreters.
At present, the most frequently used technique for analyzing reflection curvature is manual seismic geometry mapping. This technique, however, comes with associated costs and trade-offs in cycle-time, potential subjectivity, and density of observations. Methods and applications of horizon-based curvature analysis are described in numerous publications, including:
Roberts, A. (1998) Curvature Analysis: xe2x80x9cNew Attributes for the Delineation of Faults, Map Lineaments and Surface Shapexe2x80x9d, Annual AAPG, Salt Lake City, Utah, May 17-20, 1998, Extended Abstract No A553 V2.
Stewart S. A. and Podolski R. (1998), xe2x80x9cCurvature Analysis of Gridded Geologic Surfacesxe2x80x9d, in Coward M. P., Daltaban T. S. and Johnson H. (eds.), Structural Geology in Reservoir Characterization, Geological Society of London, Special Publications, 127, 133-147.
Lisle R. J. (1994), xe2x80x9cDetection of Zones of Abnormal Strains in Structures using Gaussian Curvature Analysisxe2x80x9d, AAPG Bulletin, 78, pages 1811-1819.
Zhao, P.; Pollard, D. D.; Aydin, A.; Liu, J. (1997), xe2x80x9cPrediction of Fracture Density In The Subsurface using Curvature and Composite Plate Methodsxe2x80x9d, AGU Fall Mtg, San Francisco, Dec. 8-12, 1997, Poster No. T32B-10, EOS (TRANS AGU) Vol. 78, No. 46 (Suppl), P F677, Nov. 18, 1997.
Padgett M. J. and Nester D. C, (1991) xe2x80x9cFracture Evaluation of Block P-0315, Point Arguello Field, Offshore California, using Core, Outcrop, Seismic Data and Curved Space Analysisxe2x80x9d, 1st AAPG SPE et al. Conference, Houston, Tex., pages 242-268.
Luthy S. T. and Grover G. A., (1995) xe2x80x9cThree-Dimensional Geologic Modelling of a Fractured Reservoirxe2x80x9d, Saudi Arabia, 9th SPE Middle East Oil Show, Bahrain, pages 419-430.
Belfield, W. C., xe2x80x9cPredicting Natural Fracture Distribution in Reservoirs from 3D Seismic Estimates of Structural Curvaturexe2x80x9d, SPE Rocky Mountain Reg. Mtg./Low Permeability Reservoirs Symposium, Denver, May 12-15, 2000.
Copending U.S. patent application Ser. No. 09/803,443, by Gianni Matteucci, Daniel H. Cassiani, and Larry E. Ives, xe2x80x9cMethod for Characterization of Multi-Scale Geometric Attributesxe2x80x9d, filed Mar. 9, 2001.
The publications compute principal, average, and normal curvature, or Gaussian curvature, on pre-existing gridded surfaces using gridding and finite differencing algorithms. The results of the curvature computations are used to evaluate fracture orientations and density on the basis that horizon curvature can be an indicator of the strain distribution and therefore can be related to fracture orientation and density.
However, these methods at the same time are evidence of a need for a volume-based method that does not require any pre-existing horizon interpretation or seismic gridding prior to the curvature estimation. Further, there is a need for a method that generates a full volume of reflection curvature estimates, unlike the above methods that compute curvature only on the gridded surface. Such a method would allow the interpreter to rapidly qualitatively identify mounded seismic reflection geometries or quantitatively estimate reflection curvature in a volume of seismic data.
The abstract published by Alekseev, A. S., and Burmakov, Y. A., xe2x80x9cDetermination of Spatial Parameters of Reflecting Surfaces in the Three-Dimensional Seismicsxe2x80x9d Dokl Akad Nauk SSSR Vol. 253, No. 6 pages 1339-1342, 1980, describes a method for dip and curvature characterization of seismic reflectors in 3D seismic data. However, this method is cross-correlation based and has the disadvantages of computational speed constraints and noise limitations which require appropriate filtering.
Overall, existing techniques for the qualitative identification of or quantitative estimation of geometries in seismic data are time consuming, subjective, and difficult to implement. Thus, there is a need to generate, in a computationally efficient manner, a process that enables the rapid, objective identification of seismic geometry, especially reflection curvature, so that it can be exploited in the mapping process.
The invention is a method for analyzing reflection curvature in a seismic data volume. A first horizontal direction is selected in the seismic data volume. A first length scale is selected for the horizontal gradient operators. An apparent dip value is calculated in the first direction at a plurality of dip locations from the seismic data volume. This generates a first apparent dip volume. A horizontal gradient is calculated in the first direction in the first apparent dip volume using apparent dip values at dip locations horizontally separated by a distance equal to the first length scale. This generates a first curvature volume. The process may then be repeated to generate curvature volumes for additional horizontal directions in the seismic data volume, and the individual curvature volumes may then be combined into a combined curvature volume that characterizes reflection curvature in the seismic data volume. The process may also continue with the identification of curvature regions of interest, specifically curvature size and polarity as well as amplitude size and polarity, which may then be used to extract a moundedness attribute volume.